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000-SS2 IBM Systems Software Technical Sales Mastery V1

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IBM IBM Systems Software Technical

IBM Q1 income Surpass Estimates, Revenues leave out, Down Y/Y | Real Questions and Pass4sure dumps

international enterprise Machines Corp IBM delivered first-quarter 2019 non-GAAP revenue of $4.87 per share, which surpassed the Zacks Consensus Estimate of $2.21. although, salary per share (EPS) lowered 8.2% from the year-ago quarter.

Revenues of $18.18 billion ignored the Zacks Consensus Estimate of $18.fifty two billion and declined 4.7% on a yr-over-yr basis. At regular forex (cc), the metric dipped 0.9%. The yr-over-12 months profits decline can essentially be attributed to currency fluctuation and headwinds from IBM Z product cycle. also, softness within the rising markets of Asia Pacific affected the right-line performance.

chiefly, IBM stated that signings declined 14% on cc basis in the first quarter to $7.6 billion. features backlog declined 2% yr over year and totaled $111.6 billion.

In a 12 months’s time, shares of IBM have lost 2.5% in comparison with the business’s 0.5% decline.


Geographic earnings details

Revenues from Americas decreased 1% on cc foundation, reflecting the headwind from the IBM Z product cycle. The same from Europe, center-East and Africa have been flat yr over 12 months, whereas Asia-Pacific revenues declined 2% on a year-over-12 months groundwork.

Structural alterations

ranging from first-quarter 2019, IBM combined Cloud business and Cognitive software in a single section.  extra, the company merged protection capabilities with protection application.

IBM also built-in all divested business to the other categories to be able to provide better transparency to the utility and GBS segments. The divested enterprise contains pending sales of seven application products to HCL, the sale of IBM’smarketing platform and commerce utility offerings to Centerbridge and the currently concluded sale of Seterus mortgage servicing company.

Cloud & Cognitive utility section

The Cloud & Cognitive utility phase’s revenues-external more advantageous 2% 12 months over 12 months (on cc groundwork) to $5 billion. Revenues at Cloud & Cognitive application (including cloud and information platform, Cognitive application and transaction processing) multiplied primarily due to growth in application driven with the aid of security and options, boom in records and analytics in addition to artificial intelligence (AI).

Segmental revenues referring to Cloud accelerated 10%. Cloud as-a-service income annual run fee became $2.1 billion.

Revenues from cloud and records platforms accelerated 2% year over 12 months.

IBM pointed out that the mixing of AI into offerings like customer event analytics in commerce domain and multiplied adoption of IBM Cloud inner most, which is developed on Linux containers and kubernetes. It also delivered that analytics performed well within the quarter under overview, courtesy of records science offerings and IBM Cloud deepest for statistics providing.

in addition, IBM witnessed increase in business verticals like health, key areas of analytics and protection within the quarter. Watson health witnessed huge-based mostly growth in Payer, company, Imaging and existence Sciences domains.

Revenues from Cognitive applications have been up 4% year over year, driven through safety, health, give chain and weather. security boom changed into backed by choices in orchestration, statistics safety and endpoint administration.

Transaction Processing application includes software that runs mission-essential workloads, leveraging IBM’s hardware systems. Revenues were flat on a 12 months-over-year groundwork.

Story continues

world enterprise capabilities phase

Revenues from global enterprise features-exterior segment totaled $4.1 billion, up four% from the yr-in the past quarter. The yr-over-12 months boost in the properly line changed into basically as a result of increase across all three business areas specifically consulting, application administration and international manner features.

Cloud revenues surged 25% year over 12 months. Cloud as-a-carrier salary annual run rate was $1.eight billion.

utility management revenues were flat yr over 12 months. international manner functions revenues climbed 5%. furthermore, Consulting revenues extended 9% year over year on solid efficiency of IBM’s digital business.

global technology functions phase

Revenues from technology capabilities-external decreased 3% from the 12 months-in the past quarter to $6.9 billion. Segmental revenues touching on cloud surged 13% from the year-ago quarter. Cloud as-a-carrier income annual run rate was $7.5 billion.

Infrastructure & Cloud functions’ revenues lowered 3% from the 12 months-in the past quarter. also, Technical assist services revenues declined 2% from the year-in the past quarter.

techniques Revenues

programs revenues lowered 9% on a yr-over-year basis to $1.three billion, basically due to the affect of the IBM Z product cycle and stiff competitors. Segmental revenues referring to Cloud revenues declined 15%.

IBM Z revenues decreased 38% 12 months over year.

youngsters, power revenues multiplied 9% from the year-ago quarter. The upside will also be specifically attributed to Linux and amazing adoption throughout the newest POWER9-primarily based architecture.

meanwhile, storage hardware revenues declined on weak efficiency in each excessive end and mid-range, partially offset by means of effective growth in All Flash Arrays. IBM pointed out that pricing drive within the immensely aggressive storage market is hurting revenues.

whereas working methods software revenues increased 5%, systems Hardware slumped 14% from the yr-in the past quarter.

at last, international Financing (comprises financing and used device income) revenues reduced 19% yr over year and 9% at cc to $417 million.

operating details

Non-GAAP gross margin increased one hundred foundation features (bps) from the year-in the past quarter and came in at forty four.7%. The gross margin benefited primarily from 160 bps expansion in services margin.

working fee (analysis & development prices and selling, established and administration fees) declined 10.6% year over year on attention of acquisition synergies and improving operational efficiencies. at the moment, IBM continues to invest in abruptly becoming fields like hybrid cloud, artificial intelligence (AI), safety and blockchain.

Pre-tax margin from carrying on with operations extended 320 bps on a yr-over-yr groundwork to 12.3%.

Non-GAAP working margins from continuing operations shrunk ninety bps and got here in at 11%.

steadiness Sheet & money circulate details

IBM ended first-quarter 2019 with $18 billion in total cash and marketable securities compared with $eleven.9 billion within the old quarter. total debt (including latest portion) changed into $forty nine.9 billion, up from $45.8 million from the previous quarter.

IBM pronounced money stream from operations (apart from global Financing receivables) of $four.eight billion and generated free money flow of $1.7 billion within the quarter beneath assessment.

moreover, the business back $2.3 billion to its shareholders via dividends and share repurchases. The company lower back greater than $10.3 billion to its shareholders via dividends and share repurchases for the complete 12 months.

at the end of the yr, the enterprise had $2.four billion ultimate under latest buyback authorization.


For 2019, IBM continues to are expecting non-GAAP EPS to be at the least $13.90. The Zacks Consensus Estimate is currently pegged at $13.90.

IBM nevertheless anticipates 2019 free cash circulate of $12 billion.

Zacks Rank & shares to believe

IBM at the moment includes a Zacks Rank #4 (promote).

Few more suitable-ranked stocks within the broader know-how sector are Yelp Inc. YELP, Xilinx, Inc. XLNX and general screen employer OLED, each sporting a Zacks Rank #1 (strong purchase). that you can see the complete listing of these days’s Zacks #1 Rank stocks here.

The long-time period earnings growth price for Yelp, Xilinx and widespread display is presently pegged at 18.6%, 12% and 30%, respectively.

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building the system/360 Mainframe practically Destroyed IBM | Real Questions and Pass4sure dumps

via James W. Cortada

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The IBM System/360 picture: Mark Richards/computing device historical past Museum IBM spent US $5 billion to construct the gadget/360, added in 1964. These 9-song magnetic tape drives have been among the many S/360’s a hundred and fifty-product line.

a short listing of the most transformative products of the past century and a half would include the lightbulb, Ford’s model T—and the IBM gadget/360. This mainframe series continuously modified the laptop industry and revolutionized how companies and governments labored, improving productivity and making countless new tasks feasible.

within the years leading as much as its 7 April 1964 launch, although, the 360 become probably the most scariest dramas in American company. It took an almost fanatical commitment at all tiers of IBM to bring on this spectacular assortment of machines and application. whereas the technological innovations that went into the S/360 have been vital, how they have been created and deployed bordered on disaster. The business experienced what science coverage knowledgeable Keith Pavitt referred to as “tribal battle”: individuals clashing and collaborating in a swiftly becoming business with unstable, and in some instances unknown, technologies, as uncertainty and ambiguity dogged the entire protagonists.

in the end, IBM became huge and different satisfactory in ability, staffing, financing, and materiel to be triumphant. In a nearly entrepreneurial fashion, it took competencies of emerging technologies, no matter the place they had been determined within the enterprise. In hindsight, it appeared a sloppy and sick-informed endeavor, chaotic in execution and yet brilliantly a hit. They live in an age that celebrates innovation, so inspecting instances of how innovation is performed can most effective illuminate their realizing of the procedure.

through the conclusion of the Fifties, laptop users confronted a seemingly intractable issue. Had it now not been solved, it could have prevented computers from becoming widespread, and any recommendations of residing in an tips Age would have been fiction.

IBM 1401 image: IBM The S/360 changed into designed to exchange IBM’s 1401 mainframe, which changed into everyday however couldn’t be multiplied or upgraded.

groups have been buying computer systems in outstanding numbers, automating most of the old punch card operations and doing extra with facts processing. The popularity of the IBM 1401 illustrates the swift adoption of computing. Over 12,000 of these techniques were bought from their introduction in 1959 to 1971, when IBM retired the line.

With the 1401 so dominating the desktop enterprise, any complications with it have been serious. considered one of them was that the 1401 was too small.

users discovered these machines so constructive that they saved piling greater work on them, accomplishing the system’s capacity. They then had three options: move to an even bigger IBM equipment, equivalent to an IBM 7000, install a competitor’s equipment, or acquire more 1401s. None of these options changed into pleasing. To trade to a bigger device required rewriting utility, on account that the historic application would not work on a special class of computing device. The cost of rewriting might simply exceed the monetary benefits of moving to an even bigger computing device. Such a metamorphosis also known as for retraining staff or hiring new group of workers ordinary with the new gadget. including extra units of the same system changed into equally unattractive because each and every unit required duplicate team of workers, equipment, and protection of hardware and application. consumers desired systems that had been “upgradable” or “compatible,” such that as their wants grew, they may bring in greater machines but nonetheless run the identical utility and peripheral device. in the Nineteen Fifties and early Nineteen Sixties, it became a wish, and for vendors an aspiration.

IBM had worse issues than its consumers did. The 1401s have been proving so ordinary that engineers in Endicott, N.Y., which had developed the gadget, resisted makes an attempt by using their counterparts in Poughkeepsie to build higher computer systems, leading to growing contention between the two companies. As one engineer recalled, “So severe turned into it that occasionally it seemed to exceed the competition with external rivals.” systems made through Poughkeepsie would not run classes written for the 1400 collection. shoppers eager to flow from the smaller 1400s to the higher Poughkeepsie machines put expanding power on IBM to deliver compatibility. Senior management needed to deal with the expenses of sustaining R&D for a half-dozen incompatible product strains and practicing IBMers to sell and retain so many systems.

Consensus grew that IBM vital to get right down to one gadget to simplify creation, in the reduction of the cost of R&D, and be extra competitive towards a becoming array of opponents. If valued clientele had to improve within the early 1960s, they may just as effectively movement to a competitor’s computing device, considering the fact that they would have to rewrite their utility anyway.

The vigor of compatibility became validated in the fall of 1960, when IBM brought the extra powerful 1410 to substitute the 1401. software and peripheral device for the 1401 labored with the more moderen computer. purchasers and IBM earnings adored that fact. Poughkeepsie’s engineers have been near completing work on a set of four computers universal as the 8000s that had been appropriate with the 7000s.

T. Vincent Learson photo: IBM To get the S/360 off the ground, T. Vincent Learson compelled engineering factions inside IBM to cooperate.

T. Vincent Learson—known as Vin or T.V.—was in charge of future product building because the vice president of manufacturing and construction. A gifted problem solver, he knew he needed to stream straight away to spoil down the rivalry between Endicott and Poughkeepsie. IBM’s CEO at the time, Thomas J. Watson Jr., later described what took place: “He did it by using making use of a management method referred to as ‘abrasive interplay.’ This capability forcing individuals to swap sides: taking the top engineer from the small-computing device division and making him boss of the greatest construction group in the huge-computer division. lots of people idea this made about as tons experience as electing Khrushchev president.”

Learson replaced the Poughkeepsie supervisor in charge of the 8000 mission with Bob O. Evans, who had served because the engineering manager for the 1401 and 1410. Evans appreciated compatibility throughout all future products. After 90 days in his new function, Evans recommended that work on the 8000s be stopped and that each sites start working “to improve a total cohesive product line.” He also proposed a daring new base know-how for all future systems, called solid common sense know-how (SLT), to make IBM’s machines greater competitive.

Frederick P. Brooks Jr., who led the design group for the 8000, fought returned. Evans and Brooks had been ambitious opponents. both engineers both had years of adventure working engineering and product development actions at IBM, and that they have been articulate and incredibly revered by their staffs and senior management. Brooks turned into now not as high rating as Evans, so Learson introduced in Jerrier A. Haddad, who had spent the old two years in can charge of the advanced Engineering construction Division, to analyze the proposed approaches of Evans and Brooks. Haddad recommended going with Evans’s ideas, and Learson killed the 8000 mission in may 1961.

Bob Evans immediately asked Brooks to develop the plan for a compatible family of computer systems. Brooks become flabbergasted, however he authorized, and with that both engineering communities stopped feuding and began taking part. there were nonetheless opponents in the company, but no matter—the trajectory towards a standard gadget had been set.

From left: Bob O. Evans, Frederik P. Brooks Jr., and Jerrier A. Haddad. pictures: IBM Bob O. Evans [left] suggested killing IBM’s larger 8000 mainframe in desire of a brand new line of suitable computer systems. Frederick P. Brooks Jr. [middle], who led the 8000’s design, objected, however Jerrier A. Haddad [right] sided with Evans. Evans then asked Brooks to work on the new line, which grew to be the S/360.

Learson also assigned John W. Haanstra, president of the established items Division, which produced the 1400s, to chair an interior project drive known as spread (for systems Programming, research, Engineering, and development), with Evans as vice chair. Brooks later joined the assignment drive. In December 1961, the group presented its technical recommendations.

Their document known as for 5 compatible computer systems, labeled processors (described because the computer, its reminiscence, and channels to hook up with peripheral gadget). The application and peripherals for one processor have been to work with all other processors. The plan called for the use of usual hardware and utility interfaces between computer systems and peripherals, equivalent to between disk drives and tape drives connecting to computer systems, in order that the peripherals didn't need to be swapped out when a new processor was put in. The concepts grew to be the basis for the gadget/360.

as a result of so tons can be new, the processors would now not be suitable with IBM’s latest items. That turned into an particularly essential factor. consumers moving to the new IBM machines would have to rewrite existing software only once to get on the path of the brand new gadget.

Then, IBM acquired a fortunate break. As one engineer wrote, “basically miraculously [Evans’s] vision of the new product line changed into saved with the aid of a last-minute technical accomplishment. In mid-1963, engineers within the Poughkeepsie and Endicott laboratories had begun exploring the possibility of including special microcode to the handle retailers of computer systems to increase their efficiency when simulating earlier IBM computers.” This characteristic would allow 1401 utility to run in the two smaller models of the proposed new gadget, only faster. sales acquired on board, and its executives began pressuring R&D and manufacturing management for early introduction of the brand new processors.

Watson identified what was at stake, as he recalled in his memoirs:

From the starting they confronted two risks, both of which was enough to maintain us unsleeping at nighttime. First there became the project of coordinating the hardware and application design work for the new line. They had engineering teams all over the us and Europe working concurrently on six new processors and dozens of recent peripherals…however in the conclusion all of this hardware would must plug together. The application turned into a bigger hurdle still. to ensure that gadget/360 to have a typical character, a whole lot of programmers needed to write millions of lines of computing device code. nobody had ever tackled that complicated a programming job, and the engineers have been below remarkable force to get it achieved.

A second set of problems worried manufacturing the digital accessories for the brand new programs. The electronics business became starting to work on integrated circuits, and the new computers were going to be full of these new accessories. To be unbiased, IBM had to make its own. It proved to be a pricey proposition.

at last, the company management committee, together with Watson and the board of administrators, sucked in a deep breath and accredited the spread strategies. IBM became off to the races in the wildest trip of its heritage.

IBM couldn't hide what changed into occurring. New employees flocked to Endicott, Poughkeepsie, and other labs and plant life. valued clientele heard rumors, the desktop press turned into speculating, and executives at GE, Honeywell, Sperry Univac, and in other places were attempting to assume what IBM would do.

At IBM, no person gave the impression convinced with growth on the new system. Engineering, manufacturing, income, and corporate workforce were in many cases working 100-hour weeks. Engineers moved cots into their workplaces. When Watson stopped in to see how programming become going, an engineer yelled at him to get out so he could work. The chairman of IBM beat a hasty retreat.

Left, sign in Grand Central terminal announcing train to take reporters to Poughkeepsie for the 360 press event. Right, Thoma J. Watson Jr. photos: IBM On 7 April 1964, a coach from new york metropolis’s Grand critical Terminal shuttled newshounds to Poughkeepsie, where IBM chairman Thomas J. Watson Jr. formally unveiled the equipment/360.

it all grew to be public at midday japanese time within the united states on 7 April 1964. Over 100,000 clients, newshounds, and technologists met in a hundred sixty five U.S. cities, whereas others gathered around internationally the following few days to hear the information. As Watson declared at a press convention in Poughkeepsie, it changed into “essentially the most critical product announcement within the company’s background.”

IBM 2311 disk drive photograph: Mark Richards/computer heritage Museum among the many system/360’s forty four peripherals was the 2311 disk storage power. every detachable disk pack stored 7.25 megabytes.

On that day, IBM brought a mind-boggling one hundred fifty new items: 6 computers; 44 peripherals, including tape drives, disk drives, printers, and control gadgets; and a promise to provide the software critical to make every thing work together. the press packet became an inch thick, and manuals describing the entire machines, add-ons, utility, and their installation and operation filled greater than 50 linear toes.

The central feature of the gadget/360 become, of direction, its compatibility. A growing statistics middle might installation a small 360 desktop and later upgrade to a larger one without rewriting utility or replacing peripheral device. once regularly occurring with the system, one did not must study a very good deal extra to tackle an improve. The name 360 changed into chosen to suggest the thought of 360 levels, protecting everything.

within the first month following the S/360 announcement, consumers international ordered over 100,000 techniques. to place that number in perspective, in that equal year in the united kingdom, all of Western Europe, the united states, and Japan, there have been a little more than 20,000 computer systems of any form put in. the first deliveries of the smaller machines had been promised for the third quarter of 1965, and deliveries of the higher ones within the first quarter of 1966. The extend between announcement and delivery date gave consumers time to make a decision which fashions to acquire, get them permitted and budgeted, plan on where to condominium them, teach body of workers, finished software remediation, etc. With the April announcement, IBM bought itself two years to make respectable on its promises and knock rivals back on their heels.

From 7 April to when the enterprise started supplying machines to shoppers, IBM entered probably the most dangerous, intense, and difficult period of its historical past. The company spent US $5 billion (about $40 billion nowadays) to strengthen the system/360, which at the time changed into greater than IBM made in a 12 months, and it could ultimately employ more than 70,000 new laborers. each IBMer believed that failure meant the death of IBM.

As Watson later recalled, “no longer the entire device on screen [on 7 April] became true; some contraptions were simply mockups manufactured from wood. They defined that to their guests, so there became no deception. however it was a dangerous cutting of corners—not the way I believe business have to be executed—and an uncomfortable reminder to me of how far they had to go earlier than they could name the software a success.”

Watson assigned his brother, Arthur, to control engineering and manufacturing going forward. Learson would run sales for the new gadget, “twisting the tails of their salesmen.” Tom Watson Jr. concept Learson had the more complicated task. The risk of clients converting to someone else’s machines in preference to to the S/360 vastly worried Watson.

Manufacturing in Poughkeepsie picture: IBM IBM promised to begin delivering the primary S/360 machines in the third quarter of 1965. production complications emerged almost immediately.

because the number of orders for the S/360 saved expanding, manufacturing changed into requested in 1965 to double production. One construction manager talked about it couldn't be performed and was replaced. satisfactory declined. probably the most electronic circuits within an SLT, as an example, had been not comprehensive, so electrons couldn't go where they had been speculated to. through the conclusion of the 12 months, the fine manage branch had impounded 25 percent of all SLT modules, bringing construction to a halt.

System 360 SLT held within a few fingers. image: IBM With the S/360, IBM added its solid good judgment technology (SLT), a precursor to integrated circuits. Doubling the creation of the S/360 in 1965 led to defects in 1 / 4 of the SLT modules.

After the complications had been solved, manufacturing proceeded in 1966, resulting in 90 million SLT modules bring produced, in comparison to just 36 million the previous yr. IBM opened a new plant in East Fishkill, just south of Poughkeepsie, which made extra semiconductor devices than all other producers worldwide combined. production also accelerated to new amenities in Burlington, Vt., and in Corbeil-Essonnes, France.

To get to the bottom of manufacturing issues with the ferrite-core reminiscences, IBM deploy a plant in Boulder, Colo., in 1965. but it took the craftsmanship of employees in Japan to get the creation of reminiscences up to the necessary amounts and exceptional.

IBM System 360 ferrite-core memory. photograph: Mark Richards/desktop history Museum The S/360’s ferrite-core reminiscence also proved extraordinarily tricky to fabricate. This airplane carries 1,536 reminiscence cores.

As manufacturing grew to be a worldwide effort, new complications arose in coordinating activities and fabricating machines. Arthur Watson had some journey managing IBM’s small factories outdoor the U.S. but none with resolving engineering issues, let alone large world issues in construction and manufacturing. He became out of his league, and his brother challenged him to resolve the issues. meanwhile, Learson and his sales teams wanted further advancements to the product line. relations between Learson and Arthur completely deteriorated. In October 1964, IBM introduced tremendous delays in transport products.

Tom removed Arthur from his job and became over his obligations to Learson, who in turn brought in 4 engineering managers to punch through the complications. Nicknamed the “four horsemen,” they'd full authority global for getting the S/360 manufactured and dropped at shoppers. Their collection of issues, one of the most managers noted later, become “an absolute nightmare,” “a grey blur of 24-hour days, seven days a week—not ever being home.” And yet, in 5 months, that they had labored out sufficient of the problems to start meeting delivery dates. In January 1966, Learson became president of IBM.

The “four horseman” were Henry E. Cooley, Clarence E. Frizzell, John W. Gibson, and John Haanstra. photos: IBM dealing with unacceptable production delays, Learson brought in [left to right] Henry E. Cooley, Clarence E. Frizzell, John W. Gibson, and John Haanstra, who sorted out manufacturing issues international and got the S/360 again on track.

Arthur turned into shunted into the role of vice chairman. His career changed into damaged, and he retired in 1970. In his memoirs, Tom Watson Jr. admitted to being in a virtually continuous panic from 1964 to 1966 and deeply regretted his treatment of Arthur. “I felt nothing however shame and frustrations on the method I’d treated him…. as it became, they remade the computer business with the equipment/360, and objectively it become the premier triumph of my business career. however whenever I look lower back on it, I consider about my brother I injured.”

application complications also slowed production of the 360. The application construction team of workers become described as being in “disarray” as early as 1963. The working equipment, referred to as OS/360, struggled to run more than one job at a time, which became simple to creating the S/360 speedy and productive. different complications surfaced with telecommunications and with software courses. Programming support became yet another contentious subject.

Fred Brooks volunteered to support, and IBM added 1,000 americans to the operating gadget undertaking, costing the business extra for utility in twelve months than had been planned for the entire building of the S/360 gadget. however throwing extra programmers at the undertaking didn't help. according to the S/360 event, Brooks would later extend on that theme in the mythical Man-Month (Addison-Wesley, 1975), nevertheless some of the most generally examine books on computing. The application would take years to comprehensive, but in the conclusion it worked smartly satisfactory to hold the transport prolong to 1 month.

Delivery of the IBM System/360 in to Tokai Bank Japan. photo: IBM A device/360 arrives at Tokai bank in Japan. Demand for computing grew particularly within the years following the S/360’s launch.

regardless of the costs and anxiety, in 1965—the year IBM had committed to shipping the first units to valued clientele—it managed “with the aid of some miracle” (Watson’s words) to deliver a whole bunch of medium-measurement S/360s. Their quality didn't all the time match the usual design standards. Shortages of constituents, different elements that did not work, and application crammed with bugs spread to many countries. very nearly every initial client encountered problems.

branch offices have been hiring techniques engineers to assist. SEs had been college graduates, usually with technical degrees, who knew how to debug application and assisted the sales drive in promoting and supporting computer systems. The SEs heroically tackled S/360’s utility problems, while field engineers, who put in machine, mounted hardware complications. Salesmen calmed their customers, while branch managers labored to retain their staffs encouraged and focused.

And despite the various problems, “consumers had been nevertheless ordering 360s quicker than they may construct them,” Watson recalled, forcing beginning dates out as lots as three years. via the conclusion of 1966, shoppers had taken start of 9 models of the S/360, for a total of seven,seven hundred.

IBM’s opponents replied. Burroughs, GE, Honeywell, NCR, and Sperry Rand, working largely in the u.s., CII in France, and ICT (later ICI) in extraordinary Britain brought techniques compatible with one one more’s machines, however no longer compatible with IBM’s. A 2nd, smaller group chose to manufacture machines that had been appropriate with IBM’s, together with RCA and others in Europe and Japan, counting on RCA’s licenses.

1968. Flanked by a display console with an array of lights and switches, an operator uses a monitor to check the performance of the Model 91. This System/360 installed at NASA's Goddard Space Flight Center in Greenbelt, Md. image: IBM NASA purchased a few S/360s, including this one at Goddard house Flight core. a number of others at mission manage in Houston have been used to computer screen Apollo 11.

five years later, the international stock of put in IBM computer systems had grown to $24 billion, whereas that of competitors had reached $9 billion. In other words, IBM’s S/360 accelerated universal demand for computing so vastly that it raised all boats. The business’s annual growth in the second half of the Nineteen Sixties changed into in double digits 12 months over yr, as many hundreds of corporations increased their use of computer systems. Demand for computing grew because of the technological innovations brought forth through IBM, however additionally because clients have been gathering sufficient adventure to understand a laptop’s cost in using down costs and performing new features.

IBM also grew, more than doubling from 127,000 employees global in 1962 to 265,000 with the aid of the conclusion of 1971. revenue rose from $3.2 billion in 1964 to $eight.2 billion in 1971.

Fisheye view of the IBM System 360 image: IBM The S/360 reinforced IBM’s domination of the international computer enterprise. One executive, requested no matter if the enterprise would ever take on a further such mission, spoke back, “Hell no, in no way again.”

because the S/360 was the coronary heart of plenty computing by the end of the Nineteen Sixties, its users constituted a global of their own. thousands of programmers only knew how to use software that ran on S/360s. additional thousands of information-processing personnel had worked most effective with IBM equipment, together with keypunch machines, printers, tape drives, disk drives, and application, which in many cases took years to grasp. by way of the early Seventies the computing space turned into generally an IBM world on each side of the Atlantic, within the emerging markets in Latin america, and in Japan.

Years later, when asked whether IBM would ever engage in such a large challenge once again, one govt barked out, “Hell no, on no account again.” Watson tilted toward an analogous response. Commenting in 1966, he said, “At their measurement, they can’t go 100 percent with anything else new once more,” that means anything else that large. After the 360, Watson made it a policy “under no circumstances to announce a new expertise a good way to require us to devote greater than 25 % of their creation to that know-how.”

The technology that brought out the S/360 remained enjoyable in the business, a distinct clan bonded ferociously to IBM. Careers had been made and broken, very own lives and marriages upended. IBMers didn't be aware of on the time how appreciably their items would trade the world, however they do.

Left, IBM: The Rise and Fall and Reinvention of a Global Icon. Right: Author James W. Cortada.

this text is in keeping with excerpts from IBM: the rise and Fall and Reinvention of a worldwide Icon (MIT Press, 2019).

James W. Cortada is a senior analysis fellow on the school of Minnesota’s Charles Babbage Institute. He worked at IBM for 38 years in income, consulting, managerial, and analysis positions.

IBM's Mainframe revenue Crashed. That’s general. | Real Questions and Pass4sure dumps

One purpose IBM (NYSE:IBM) suffered a income decline in the first quarter become slumping demand for its mainframe computer systems. earnings from mainframes tumbled 38% year over yr, dragging income within the methods segment down 9% on a foreign money-adjusted foundation.

whereas mainframes are not as vital to IBM these days as they had been during the past, the hulking methods, with a big deploy base and significant switching fees, are a key part of the business's aggressive merits. That makes the steep decline in revenue seem to be all the more concerning.

IBM's z14 mainframe system.

photo source: IBM.

this is commonplace

there isn't a cause to be concerned about the precipitous decline in mainframe earnings. IBM's mainframe income spike every time the enterprise launches a new model -- the third quarter of 2017 marked the birth of the newest surge in sales with the z14 device. After four or five quarters of robust 12 months-over-year boom, driven by means of consumers upgrading from older models, that growth is lapped, and earnings start to decline.

This cycle has played out diverse instances during the last decade as IBM refreshed its mainframe systems every few years. And despite the steep sales declines IBM is now seeing, the existing cycle is the strongest in decades.

A chart showing IBM's year-over-year mainframe growth.

Date supply: IBM. Chart through creator.

"we're seven quarters into the z14 cycle and the application continues to tune forward of the prior application. They had amazing boom in volumes or shipped MIPS, and new workload MIPS proceed to outpace their regular MIPS," mentioned IBM CFO James Kavanaugh all the way through the primary-quarter earnings call. (MIPS stands for million instructions per 2nd, a measure of processing power.)

Kavanaugh delivered that the single-frame version of the z14, launched ultimate yr and designed to healthy into commonplace statistics facilities, is a growth driver for the mainframe enterprise.

IBM more than doubled mainframe earnings on a yr-over-year basis in the 2d quarter of 2018, so an additional large decline in income within the second quarter of this 12 months is inevitable. The enterprise will then begin to lap these declines within the second half of this year.

Given the usual hole between mainframe launches, IBM's next-gen mainframe equipment doubtless won't arrive until someday in 2020. That potential three or 4 more quarters of weak mainframe performance earlier than one other yr-lengthy surge in income.

2020 is shaping up to be a big yr

now not simplest will IBM possible get a salary enhance in 2020 thanks to the next mainframe launch, but the company will additionally add just a few billion dollars of income from its acquisition of red Hat. That deal is scheduled to close earlier than the end of this year.

pink Hat is starting to be at a double-digit rate, and its utility strengthens IBM's hand as it goes after the hybrid cloud computing market. there is a mainframe connection right here, too -- crimson Hat offers a version of its enterprise Linux operating gadget for IBM's mainframes. Kavanaugh cited all over the income call that Linux is a key increase driver for the mainframe company.

IBM's complete income will doubtless decline this year, frequently because of a big foreign money headwind, but also because of slumping mainframe income. however next yr will seem lots greater.

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IBM Offers Vertical Industry Focus to ISVs, SIs, VARs | real questions and Pass4sure dumps

IBM has rolled out three new skills initiatives to help its software channel partners capture more high-margin revenue from vertical industry opportunities. In addition, the company introduced its first skills programs for software developers and further expanded industry support for software resellers.

The initiatives will provide training and resources for partners to build expertise and skills in specific industries including financial services, telecom, healthcare, retail and energy and utilities. In addition, partners can achieve a cross-industry authorization to sell security solutions based on IBM software.

For ISV’s the new program offers the most new benefits.  IBM Industry Solutions Specialty is the first partner program for independent software vendors (ISVs) focused on nine industries including banking, healthcare, and retail.  Under the new program, qualifying partners will receive:

  • Access to new technology resources and IBM Innovation Centers including cloud and mobile application development
  • Dedicated IBM experts and technical advocates to speed application development and delivery to joint customers
  • Business development and demand generation funding for industry-specific marketing campaigns
  • Opportunities for co-selling and industry event participation.
  • The new IBM Industry Solutions Specialty will help partners leverage IBM Industry Frameworks, industry-specific reference guides that help bridge the gap between general purpose middleware expertise and industry-specific business applications. Industry Frameworks have now been expanded to include hardware, IBM said. Since their introduction in 2008, more than 150 ISVs have brought to market applications based on the IBM frameworks, according to IBM.

    IBM’s Mike Riegel, vice president for ISVs and developer relations offered Channel Insider some examples of applications created by IBM software partner ISVs. For instance, he said, CareFX is a medical healthcare solution provider that has a healthcare application that works with IBM’s healthcare industry framework, he said. Their work with Boston Medical has helped improve patient referral times and patient wait times.

    IBM has also introduced an IBM Industry Authorization initiative for resellers and system integrators with deep industry skills and solutions built with IBM software. IBM said it’s an extension of the IBM Software Value Plus program, announced earlier this year, that helps software partners build sales, technical and marketing skills on IBM's software portfolio.   

    IBM partners must pass two IBM Industry Mastery tests to demonstrate their solution aligns with IBM Industry Frameworks or strategy, and offer successful client implementations

    Those who fulfill the requirements are eligible for the following:

  • Additional funding for industry specific co-marketing activities
  • Priority access to industry-focused technical enablement and industry assets
  • A dedicated executive advocate to represent partners across IBM and with customers
  • Ability to use the "Authorized Software Value Plus - Industry" designation
  • In addition, the IBM Security Authorization for business partners participating in the Software Value Plus program, helps partners develop industry-specific  skills to help customers take a comprehensive approach to IT security via a mix of sound policy, best practices and end-to-end technologies based on IBM software, IBM said

    Benefits include the following:

  • Authorization to sell a broad range of security solutions based on IBM software including InfoSphere, IBM Internet Security Solutions, Optim, Rational, Tivoli and WebSphere
  • Additional financial incentives on security software sales
  • Ability to use "Authorized Software Value Plus - Security" designation
  • A recent IBM developerWorks survey of more than 2,000 IT professionals in 87 countries found that 90 percent said they believe it is important to possess vertical industry-specific skills for their jobs, yet 63 percent admit they are lacking the industry knowledge needed to remain competitive.

    Jessica Davis covers the channel for eWeek and Channel Insider. Her technology journalism career began well before anyone heard of the World Wide Web and has included stints at Infoworld, Electronic News/EDN, and the Philadelphia Business Journal. Her work has also appeared on CNN and She has covered hardware, software and networking, as well as the business side of technology. She has won several journalism awards, including a national ASBPE award for best staff-written column, and was named Marketing Computers hardest working tech journalist on their inaugural list of top tech journalists. Jessica can be reached at

    KenSci: Using Artificial Intelligence and Machine Learning to Save Lives | real questions and Pass4sure dumps


    While using artificial intelligence and machine learning to optimize health care isn’t a novel concept, KenSci proclaims its mission is more broadly to fight death with data science. By collecting big data, analyzing variables and outcomes, and suggesting cost-effective and successful solutions, KenSci is aiding medical professionals in fending off the grim reaper. Keys to the company’s success is its ability to provide customers proof of a return on investment while improving patient outcomes, as well as providing an easy path for integrating right into the systems a hospital or health facility already uses. 

    AI and health care is an active field for investing, as many companies try to tackle outcomes cross optimized with costs, and venture capitalists are paying up. According to Frost & Sullivan, the AI health market is expected to reach $6.6 billion by 2021, growing at a compound annual growth rate of 40 percent. Accenture believes that key clinical health AI applications can potentially create $150 billion in annual savings for the United States healthcare economy by 2026. 

    As an example of a recent investment, in January, Health Catalyst raised $100 million at a lofty $1 billion valuation given sales of just $110 million in 2018. This brings its total funding to $392 million. In its recent round, funding was comprised of $85 million in debt and $15 million in equity and is being used to invest in development of its data platform and increase its clinical, financial, and operational consultative teams. It touts sepsis treatment as an example where it has most successfully used AI and patient data to improve outcomes. The key has been to identify and treat correctly it as quickly as possible. This includes rapid diagnosis and making sure the correct treatment is executed. Customers can then track how compliance achieved better outcomes and saved lives.

    While most companies are tackling care from the enterprise side, there are even consumer facing companies using AI to help users diagnose themselves. For example, K Health provides an app that asks users questions and then compares them with over a billion AI analyzed patent records to suggest possible causation and even treatment. Founded in 2016, it has already raised $44 million and has partnered with primary care providers to help drive patients to doctors when necessary.

    Not all companies using AI in healthcare are venture-backed startups. IBM (IBM) has a big push in this area via its Watson Health division. The company offers a wide range of solutions for the health care vertical market and has select offerings using AI such as its AI Patient Companion for Hospitals. It is a turnkey solution leveraging IBM Watson and other AI technology to help improve patient outcomes, reduce labor costs, and increase hospital revenue. Labor is the biggest component of a hospital’s costs and nurses are the largest subset. This system, with a Siri type interface, answers questions for patients thus decreasing nursing labor. These questions could be things such as “When am I scheduled to go down for X-rays?” or “What is the lunch menu?” Another AI based offering is Micromedex with Watson that had been used to allow natural language queries of drug databases to help pharmacists get quick answers for drug classes, dosing and administration, medication safety, mechanism of action, pharmacokinetics and drug interactions. 

    NVIDIA (NVDA) also has a big healthcare push fueled by imagery in diagnostics that requires high-end graphics processing, its forte. It has introduced its Clara platform that enables developers to build and deploy medical imaging applications. It is the foundation to enable of intelligent instruments and automated healthcare workflows. NVIDIA takes what it learned in the graphics required for gaming and helps customers apply it to the medical imaging industry. Its SDK has been used for processing for medical reconstruction, image processing and rendering, and computational workflows for CT, MRI, and ultrasound images. In November, the company announced it is working with GE Healthcare and Nuance to bring artificial intelligence to their medical imaging solutions. The companies plan to integrate GE installed base of 50,000 machines onto NVIDIA’s platform, and to accelerate the creation and use of deep learning algorithms for its instruments. Nuance plans to bring machine learning to radiologists and data scientists through its AI Marketplace for Diagnostic Imaging, which has been built on NVIDIA’s deep learning platform. It will create algorithms to help the workflow of the radiologists, aiding them to detect and quantify clinical findings more quickly and improve care. Nuance has a large installed base of image-sharing and reporting solutions, and they are now used by 70% of radiologists.

    In contrast to the focus on these two large companies, KenSci is more like Health Catalyst. However Health Catalyst has focused on building a data warehouse architecture and uses analytics, while KenSci has focused on AI and machine learning to improve algorithms utilizing the science where its founders excel. Two friends from India, who both earned degrees in computer science from Maharaja Sayajirao University, co-founded KenSci in 2015. KenSci is based in Seattle, Washington and has offices in India and Singapore. Its CEO, Samir Majure, has an MS in Computer Science from Perdue and a Wharton MBA. Before co-founding KenSci, he spent 17 years at Microsoft. In his last position there he managed a portfolio of CRM products and integrated online services for marketing and sales. He also successfully launched new innovative products in Small Business CRM category. In this role he had direct responsibility for managing a multi-discipline product unit of about 75 people, who included developers, program managers, and professionals in Quality Assurance, User Experience and User Assistance. The second co-founder, and the current CTO of KenSci, is Ankur Teredesai. In addition to his role at KenSci, he is a professor at the University of Washington in Seattle where he teaches applied machine learning and is Executive Director of the school’s Center for Data Science. 

    KenSci was incubated at University of Washington's Center for Data Science at University of Washington Tacoma, and designed on the cloud with help from Microsoft's Azure4Research grant program. The company got its start with grants from DARPA and NASA JPL, and partnerships with leading Health agencies like The Center for Disease Control. The KenSci platform is a set of services that are built on Microsoft Azure ML, SQL and uses Power BI. The services make it easy for machine learning workloads especially in healthcare. It is essentially a scoring platform at the heart of it, but it also has services that make it easy to develop models. It also has bank of service features out of the box with pre-implemented models to be used as a starting point. Today the company employs about 60 people with 90% located in Seattle. It has projects worldwide and boasts projects in the UK, Singapore and India where is seeks to expand further. In fact, during 2018 the company doubled in size.

    KenSci had used AI and machine learning to predict the course of a variety of medical issues as shown below, including diabetes, CHF, COPD, CKD, and sepsis. The company's platform is based on a database of over 150 machine learning model and the algorithms are developed based on over 10 million sets of data. These data sets are clinical data (medical records), financial data (insurance and health care costs) and patient biometric data (for example heart rate). KenSci software reorders and analyzes the patient data to identify patterns that may indicate potential risks and provide predictive information. This technology can then be used to reduce the rate of hospital readmission of patients.

    The platform has been used for a variety of custom solutions too. It has:• Improved emergency department staffing and patient experience at Rush University Medical Center• Identified lifetime healthcare costs for 9/11 first responders for the Center for Disease Control (CDC)• Reduced the cost of prescriptions at a system level without sacrificing quality for Beaumont Health in Michigan• And created risk stratification and readmission predictions for military personnel for the Madigan Army Medical Center.

    One fascinating project the company took on using CDC data is a look at predicting the opioid crisis using historical data from 1999 to 2015. By taking data from all US counties, the company is able to predict how widespread the problem may become in a few short years as deaths are increasing logarithmically throughout the country with current hotspots in New Mexico and Appalachia.

    On Friday, the company announced it had raised its second round of financing. It raised $22 million in Series B funding. The round was led by Polaris Partners, and was joined by investors UL ventures and included additional funding from Ignition Partners, Osage University Partners, and Mindset Ventures. This round brings KenSci's total funding to $30.5 million. 

    Back in January of 2017, the company raised $8.5 million in a Series A round led by Bellevue-based firm Ignition Partners, and included Osage University Partners and Mindset Ventures. The company used the funds to increase its workforce and invest in sales, marketing and customer service to support more customers. 

    With its new capital it has quickly moved to strengthen its staff. On the 23rd of January, it announced four strategic hires in engineering. All four have experience in AI, healthcare and cloud solutions for enterprises.

    The new hires are:• Sudarshan Chitre, former Vice President of Engineering at Oracle, who brought with him 20 years of experience building software for enterprise and consumers. In his career, he has had the opportunity to lead teams of exceptional engineers to build v1 cloud platform services for Azure (HDinsight) and AWS (Internet of things). He was also the technical co-founder of Brimbee and held various roles at Amazon. He began his career at Microsoft where he spent 16 years.

    • Ryan Brush, former Distinguished Engineer at Cerner, spent the last several years there on data engineering, analysis, and the application of very large healthcare datasets. He created Clara, an open source rules engine, Bunsen, an open source library for large-scale analysis of FHIR datasets, and has spoken at conferences including Strata, Strangeloop, ApacheCon, FHIR DevDays, and others. As an author, Ryan has contributed chapters to the books 97 Things Every Programmer Should Know and Hadoop: The Definitive Guide.

    • Neelesh Kamkolkar, former Lead of Product Management at Tableau, brought over 15 years of experience building platforms, solutions, and services. Most recently, he led enterprise product management at Tableau Software, where he built a platform that enabled data analytics to be accessible to everyone in a secure, scalable way. 

    • Tim Kellogg, former Senior Software Engineer, at Amazon Web Services, brought with him over a decade of experience. As an experienced full stack software engineer with a proven track record of building performance-critical systems, Tim has a comprehensive knowledge of garbage collection and JIT compilation in .NET that he has used to build scalable applications in C#.

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    Can Anyone Stop Amazon from Winning the Industrial Internet? | real questions and Pass4sure dumps

    Executive Summary

    Digital natives like Amazon have already disrupted industries such as media, publishing, travel, music, and photography. But who is likely to assume leadership in creating and capturing economic value in Type 3 products (products which have physical components, “smart” components, and connectivity)? If digital natives want to develop software-enabled solutions that siphon off significant value from industrial hardware, they must overcome three barriers: the physics of the hardware, customer intimacy, and difficulty in sharing risks. Likewise, if industrial giants want to lead in the industrial internet they will need to overcome their three barriers: software talent, digital culture, and the incumbent’s dilemma. Among the tech giants, Amazon is a likely winner in the Industrial Internet, as it has successfully fused physical with digital. Amazon understands the economic laws of analog products and is not afraid of massive up-front investments and slower growth.

    Just the announcement that Jeff Bezos, Warren Buffett, and Jaime Dimon will be entering the health care space has sent shock waves for industry incumbents such as CVS, Cigna, and UnitedHealth. It also puts a fundamental question back on the agendas of CEOs in other industries: Will software eat the world, as Marc Andreessen famously quipped? Is this a warning shot that signals that other legacy industrial companies, such as Ford, Deere, and Rolls Royce are also at increased risk of being disrupted?

    To start to answer that question, let’s tally up the score. There are three types of products today. Digital natives (Amazon, Google, Facebook, Microsoft, IBM) have gained competitive advantage in the first two, and the jury is still out on the third:

  • Type 1: These are “pure” information goods, where digital natives rule. An example would be Google in search, or Facebook in social networking. Their business models benefit from internet connectivity and they enjoy tremendous network effects.
  • Type 2: These are once-analog products that have now been converted into digital products, such as photography, books, and music. Here too, digital natives dominate. These products are typically sold as a service via digital distribution platforms ( for books, Spotify for music, Netflix for movies).
  • Type 3: Then there are products where input-output efficiency and reliability of the physical components are still critical but digital is becoming an integral part of the product itself (in effect, computers are being put inside products). This is the world of the Internet of Things (IOT) and the Industrial Internet.
  • Manufacturing-heavy companies such as Caterpillar, Ford, and Rolls Royce compete in this world. An aircraft engine is unlikely to become a purely digital product any time soon! Such products have three components: physical components, “smart” components (sensors, controls, microprocessors, software, and enhanced user interface), and connectivity (one machine connected to another machine; one machine connected to many machines; and many machines connected to each other in a system).

    Digital natives have already disrupted industries such as media, publishing, travel, music, and photography. But who is likely to assume leadership in creating and capturing economic value in Type 3 products: Digital natives or industry incumbents? Ford or Tesla? Rolls Royce or IBM? Caterpillar or Microsoft? Amazon, Berkshire Hathaway and JPMorgan Chase combine or UnitedHealth?

    The Challenges for Digital Natives

    Value will no doubt be created in the era of smart, connected machines. They don’t expect Amazon or Microsoft or IBM to design, make, and market agricultural tractors, aircraft engines, or MR scanners. The question really is: Can digital natives develop software-enabled solutions that siphon off significant value from industrial hardware? The answer is “yes.” But it won’t be easy. It will require tremendous amounts of investments in building new capabilities for hardware companies like HP, Cisco, Dell, Samsung, and Lenovo; established software companies like Facebook, Google, Amazon, and Microsoft; and start-ups. In particular, there are three barriers they must overcome:

    1. The physics of the hardware. Companies like Rolls Royce design and manufacture jet engines. These are very complicated machines. There is hard science behind these machines. That’s much different than digital natives like Airbnb where marketing is more important than technical expertise.

    Industry incumbents have expertise in the material sciences, for instance. Further, scientific knowledge keeps improving over time. They have made heavy R&D investments—both basic and applied—to remain at the cutting-edge of the physics of the hardware. Much of this scientific knowledge is protected by patents.

    Mastery of hard science is a pre-requisite to develop software-based solutions on the hardware. These companies’ superior product/domain knowledge provides them the comparative advantage to model the asset’s performance and write high-end/high value-added software applications. A “pure” digital company can write commodity software applications. But it must acquire enough capabilities on the physics to write sophisticated apps that improve assets’ performance.

    2. Customer intimacy. Industrial giants have well-established brands, built strong customer relationships, and signed long-term service contracts. They’ve won the customer’s trust, which is why customers are willing to share data. Digital natives can work with industrial customers, but they have to first earn their trust; they must build capabilities to understand customer operations; they must match the industrials’ cumulative learning from customer interactions; they must learn to ask for the right data; and they have to hire experts in several verticals that can turn data into insights.

    3. Difficulty in sharing risks. Industrial incumbents have product knowledge, customer relationships, and field engineers on customer sites. Companies like Rolls Royce can, therefore, offer outcome deals where they guarantee customer outcomes (examples: zero downtime, higher speed, more fuel efficiency, zero operator error, greater reliability) and share risks and rewards with customers. It would be very hard for Amazon or Google to guarantee customer outcomes and take risks with businesses whose operations they know little about.

    The Challenges for Industrial Giants

    Can the industrial giants lead in the Industrial Internet? The answer is “yes.” But it won’t be easy for them, either. They too have three significant barriers to overcome:

    1. Software talent: The IT talent in industrial companies can execute projects oriented towards process efficiency and cost reduction. That talent is ill-suited to develop new, breakthrough software products that offer superior customer outcomes. For that end, they must be able to attract world-class innovators and software engineers. Is, say, Rolls Royce, in the same consideration set as Facebook and Google for young tech employees? Not, really. If so, how can the industrial giants compete to attract the best talent?

    2. Digital culture: Industrial businesses and digital businesses operate with completely different principles. The characteristics of hardware businesses include long product development cycle, Six Sigma efficiency, and long sales cycle. Software businesses have different characteristics: short product development cycle, flexibility, and short sales cycle. The industrials must build a digital culture based on concepts like lean, agile, simplicity, responsiveness, and speed. That’s a tall order for an established enterprise.

    3. The Incumbent’s Dilemma: Digital has the potential to disrupt industrial businesses. There are three ways digital strategy can cannibalize “core” industrial business. First, data and insights can help improve the productivity of machines; digital, therefore, has the potential to cannibalize future hardware sales. Second, data and insights increase the reliability of machines; digital therefore has the potential to cannibalize future service revenues. Third, software subscription and license might enable customers to do self-service. Current customers could terminate/renegotiate service contracts, and potential customers may not enter into service contracts at all. In short, it is very difficult for a company to disrupt itself.

    The future of the Industrial Internet will involve partnerships across a variety of players including tech companies and industrial companies. The key issue: Who will assume the leadership position to extract maximum economic value in such an ecosystem? Will industrial companies take the lead? Or will the digital natives take the lead? Both have a chance.

    If I were a betting man, I would place my bets on tech giants over industry incumbents. One factor that will favor digital companies in the industrial internet is technological/scientific breakthroughs that level the playing field for newcomers. For example, breakthroughs in battery technology made the electric cars possible. Electric cars are much simpler to design than cars with internal combustion engines, allowing Tesla and BYD to enter the market despite Ford’s decades of expertise. Since electrification and driverless cars go together, other tech companies such as Google, Baidu, Apple, and Lyft will also be able to enter the automotive market. Similar technological changes in jet engines and agricultural tractors can allow tech giants to gain foothold in these industries as well.

    More importantly, Amazon or Google have the resources to acquire the capabilities to master the physics and acquire customer relationships and compete with the industrial giants in the Industrial Internet. They have enough resources and some to buy them, if needed.

    Among the tech giants, Amazon is a likely winner in the Industrial Internet. It has successfully fused physical with digital. Amazon understands the economic laws of analog products and is not afraid of massive up-front investments and slower growth. Its acquisition of Whole Foods and experiments with Amazon Go grocery stores are an example. Amazon is the one company everyone’s scared of, even industrial giants.

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